Summarization from Medical Documents: A Survey
Stergos D. Afantenos, Vangelis Karkaletsis, Panagiotis Stamatopoulos

TL;DR
This survey reviews recent advances in medical document summarization, highlighting techniques, challenges, and future directions for handling large, multilingual, and personalized medical data sources.
Contribution
It provides a comprehensive overview of summarization methods applied to medical documents and discusses future research challenges and opportunities in the field.
Findings
Medical summarization techniques vary across document types.
Challenges include scaling, personalization, and multilingual support.
Future research should focus on practical application integration.
Abstract
Objective: The aim of this paper is to survey the recent work in medical documents summarization. Background: During the last decade, documents summarization got increasing attention by the AI research community. More recently it also attracted the interest of the medical research community as well, due to the enormous growth of information that is available to the physicians and researchers in medicine, through the large and growing number of published journals, conference proceedings, medical sites and portals on the World Wide Web, electronic medical records, etc. Methodology: This survey gives first a general background on documents summarization, presenting the factors that summarization depends upon, discussing evaluation issues and describing briefly the various types of summarization techniques. It then examines the characteristics of the medical domain through the…
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